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NVIDIA PyTorch/CUDA Job #40

NVIDIA PyTorch/CUDA Job

NVIDIA PyTorch/CUDA Job #40

name: NVIDIA PyTorch/CUDA Job
on:
workflow_dispatch:
inputs:
script_content:
description: 'Content of Python/CUDA script (.py or .cu file)'
required: true
type: string
filename:
description: 'Name of script (supports .py or .cu)'
required: true
type: string
jobs:
train:
runs-on: [gpumode-nvidia-arc]
timeout-minutes: 10
container:
image: nvidia/cuda:12.4.0-devel-ubuntu22.04
steps:
# Create script using shell echo
- name: Create script file
run: |
cat << 'EOF' > ${{ github.event.inputs.filename }}
${{ github.event.inputs.script_content }}
EOF
- name: Setup Python environment
if: endsWith(github.event.inputs.filename, '.py')
uses: actions/setup-python@v4
with:
python-version: '3.10'
- name: Install uv
if: endsWith(github.event.inputs.filename, '.py')
uses: astral-sh/setup-uv@v3
with:
version: "latest"
- name: Setup Python venv
if: endsWith(github.event.inputs.filename, '.py')
run: |
uv venv .venv
echo "VIRTUAL_ENV=$PWD/.venv" >> $GITHUB_ENV
echo "$PWD/.venv/bin" >> $GITHUB_PATH
- name: Install dependencies
if: endsWith(github.event.inputs.filename, '.py')
run: |
if grep -rE "(import torch|from torch)" "${{ github.event.inputs.filename }}"; then
echo "PyTorch detected, installing torch"
uv pip install numpy torch
fi
if grep -rE "(import triton|from triton)" "${{ github.event.inputs.filename }}"; then
echo "Triton detected, installing triton"
uv pip install triton
fi
- name: Run script
run: |
if [[ "${{ github.event.inputs.filename }}" == *.cu ]]; then
# Compile and run CUDA file
nvcc "${{ github.event.inputs.filename }}" -o cuda_program
./cuda_program > training.log 2>&1
else
# Run Python file
python3 "${{ github.event.inputs.filename }}" > training.log 2>&1
fi
- name: Upload training artifacts
uses: actions/upload-artifact@v4
if: always()
with:
name: training-artifacts
path: |
training.log
${{ github.event.inputs.filename }}
env:
CUDA_VISIBLE_DEVICES: 0 # Make sure only one GPU is used for testing